From 0234a95fd7685362efe0071862f2a35517d439ea Mon Sep 17 00:00:00 2001 From: imClumsyPanda Date: Sat, 15 Apr 2023 10:34:54 +0800 Subject: [PATCH] update README.md and README_en.md --- agent/__main__.py | 18 --- .../chatglm_with_shared_memory_openai_llm.py | 128 ------------------ ceshi-dev.txt | 0 ...hatglm_with_shared_memory_openai_llm.py.py | 22 --- 4 files changed, 168 deletions(-) delete mode 100644 agent/__main__.py delete mode 100644 agent/chatglm_with_shared_memory_openai_llm.py delete mode 100644 ceshi-dev.txt delete mode 100644 test/test_chatglm_with_shared_memory_openai_llm.py.py diff --git a/agent/__main__.py b/agent/__main__.py deleted file mode 100644 index 4f2dc19..0000000 --- a/agent/__main__.py +++ /dev/null @@ -1,18 +0,0 @@ - -from .chatglm_with_shared_memory_openai_llm import * - -if __name__ == "__main__": - # 创建 ChatglmWithSharedMemoryOpenaiLLM 类的实例 - chatglm_instance = ChatglmWithSharedMemoryOpenaiLLM() - - # 使用代理链运行一些示例输入 - chatglm_instance.agent_chain.run(input="我跟露露聊了什么?") - chatglm_instance.agent_chain.run(input="她开心吗?") - chatglm_instance.agent_chain.run(input="她有表达意见吗?") - chatglm_instance.agent_chain.run(input="根据历史对话总结下?") - chatglm_instance.agent_chain.run(input="""可以拓展下吗?，比如写个小作文。 - 大纲：游戏的美好回忆，触不可及的距离，不在乎得失 - 主题：露露的陪伴无比珍贵 - 背景：游戏，通话，当下 - 开篇需要以游戏相识你挑逗的话语讲起 - """) diff --git a/agent/chatglm_with_shared_memory_openai_llm.py b/agent/chatglm_with_shared_memory_openai_llm.py deleted file mode 100644 index 0d90a17..0000000 --- a/agent/chatglm_with_shared_memory_openai_llm.py +++ /dev/null @@ -1,128 +0,0 @@ -import torch -from langchain.agents import ZeroShotAgent, Tool, AgentExecutor -from langchain.llms import OpenAI -from langchain.memory import ConversationBufferMemory, ReadOnlySharedMemory -from langchain.chains import LLMChain, RetrievalQA -from langchain.embeddings.huggingface import HuggingFaceEmbeddings -from langchain.prompts import PromptTemplate -from langchain.text_splitter import CharacterTextSplitter -from langchain.vectorstores import Chroma -from langchain.document_loaders import TextLoader -from models import ChatGLM -import sentence_transformers -import os -import readline -from pathlib import Path - - -class ChatglmWithSharedMemoryOpenaiLLM: - - def __init__(self, params: dict = None): - params = params or {} - self.embedding_model = params.get('embedding_model', 'text2vec') - self.vector_search_top_k = params.get('vector_search_top_k', 6) - self.llm_model = params.get('llm_model', 'chatglm-6b') - self.llm_history_len = params.get('llm_history_len', 10) - self.device = 'cuda' if params.get('use_cuda', False) else 'cpu' - self._embedding_model_dict = { - "ernie-tiny": "nghuyong/ernie-3.0-nano-zh", - "ernie-base": "nghuyong/ernie-3.0-base-zh", - "text2vec": "GanymedeNil/text2vec-large-chinese", - } - self._llm_model_dict = { - "chatglm-6b-int4-qe": "THUDM/chatglm-6b-int4-qe", - "chatglm-6b-int4": "THUDM/chatglm-6b-int4", - "chatglm-6b": "THUDM/chatglm-6b", - } - self.init_cfg() - self.init_docsearch() - self.init_state_of_history() - self.summry_chain, self.memory = self.agents_answer() - self.agent_chain = self.create_agent_chain() - - def init_cfg(self): - self.chatglm = ChatGLM() - self.chatglm.load_model(model_name_or_path=self._llm_model_dict[self.llm_model]) - self.chatglm.history_len = self.llm_history_len - self.embeddings = HuggingFaceEmbeddings(model_name=self._embedding_model_dict[self.embedding_model],) - self.embeddings.client = sentence_transformers.SentenceTransformer(self.embeddings.model_name, - device=self.device) - - def init_docsearch(self): - doc_path = str(Path.cwd() / "content/state_of_the_search.txt") - loader = TextLoader(doc_path) - documents = loader.load() - text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0) - texts = text_splitter.split_documents(documents) - docsearch = Chroma.from_documents(texts, self.embeddings, collection_name="state-of-search") - self.state_of_search = RetrievalQA.from_chain_type(llm=self.chatglm, chain_type="stuff", retriever=docsearch.as_retriever()) - - def init_state_of_history(self): - doc_path = str(Path.cwd() / "content/state_of_the_history.txt") - loader = TextLoader(doc_path) - documents = loader.load() - text_splitter = CharacterTextSplitter(chunk_size=100, chunk_overlap=0) - texts = text_splitter.split_documents(documents) - docsearch = Chroma.from_documents(texts, self.embeddings, collection_name="state-of-history") - self.state_of_history = RetrievalQA.from_chain_type(llm=self.chatglm, chain_type="stuff", retriever=docsearch.as_retriever()) - - def agents_answer(self): - template = """This is a conversation between a human and a bot: - - {chat_history} - - Write a summary of the conversation for {input}: - """ - - prompt = PromptTemplate( - input_variables=["input", "chat_history"], - template=template - ) - memory = ConversationBufferMemory(memory_key="chat_history") - readonlymemory = ReadOnlySharedMemory(memory=memory) - summry_chain = LLMChain( - llm=self.chatglm, - prompt=prompt, - verbose=True, - memory=readonlymemory, # use the read-only memory to prevent the tool from modifying the memory - ) - return summry_chain, memory - - def create_agent_chain(self): - tools = [ - Tool( - name="State of Search QA System", - func=self.state_of_search.run, - description="当您需要搜索有关问题时非常有用。输入应该是一个完整的问题。" - ), - Tool( - name="state-of-history-qa", - func=self.state_of_history.run, - description="跟露露的历史对话 - 当提出我们之间发生了什么事请时，这里面的回答是很有用的" - ), - Tool( - name="Summary", - func=self.summry_chain.run, - description="useful for when you summarize a conversation. The input to this tool should be a string, representing who will read this summary." - ) - ] - - prefix = """你需要充当一个倾听者,尽量回答人类的问题,你可以使用这里工具,它们非常有用:""" - suffix = """Begin! - - {chat_history} - Question: {input} - {agent_scratchpad}""" - - prompt = ZeroShotAgent.create_prompt( - tools, - prefix=prefix, - suffix=suffix, - input_variables=["input", "chat_history", "agent_scratchpad"] - ) - - llm_chain = LLMChain(llm=OpenAI(temperature=0), prompt=prompt) - agent = ZeroShotAgent(llm_chain=llm_chain, tools=tools, verbose=True) - agent_chain = AgentExecutor.from_agent_and_tools(agent=agent, tools=tools, verbose=True, memory=self.memory) - - return agent_chain diff --git a/ceshi-dev.txt b/ceshi-dev.txt deleted file mode 100644 index e69de29..0000000 diff --git a/test/test_chatglm_with_shared_memory_openai_llm.py.py b/test/test_chatglm_with_shared_memory_openai_llm.py.py deleted file mode 100644 index 052a5b0..0000000 --- a/test/test_chatglm_with_shared_memory_openai_llm.py.py +++ /dev/null @@ -1,22 +0,0 @@ - -import sys -import os - -sys.path.append(os.path.dirname(os.path.abspath(__file__)) + '/../') -from agent import ChatglmWithSharedMemoryOpenaiLLM - -if __name__ == "__main__": - # 创建 ChatglmWithSharedMemoryOpenaiLLM 类的实例 - chatglm_instance = ChatglmWithSharedMemoryOpenaiLLM() - - # 使用代理链运行一些示例输入 - chatglm_instance.agent_chain.run(input="我跟露露聊了什么?") - chatglm_instance.agent_chain.run(input="她开心吗?") - chatglm_instance.agent_chain.run(input="她有表达意见吗?") - chatglm_instance.agent_chain.run(input="根据历史对话总结下?") - # chatglm_instance.agent_chain.run(input="""可以拓展下吗?，比如写个小作文。 - # 大纲：游戏的美好回忆，触不可及的距离，不在乎得失 - # 主题：露露的陪伴无比珍贵 - # 背景：游戏，通话，当下 - # 开篇需要以游戏相识你挑逗的话语讲起 - # """)